TY - CHAP

T1 - Improving strategies in stochastic games

AU - Flesch, J.

AU - Thuijsman, F.

AU - Vrieze, O.J. J

PY - 1998

Y1 - 1998

N2 - In a zero-sum limiting average stochastic game, we evaluate a\nstrategy π for the maximizing player, player 1, by the reward φ\ns(π) that π guarantees to him when starting in state s.\nA strategy π is called non-improving if\nφs(π)⩾φs(π[h]) for any state s\nand for any finite history h, where π[h] is the strategy π\nconditional on the history h; otherwise the strategy is called\nimproving. We investigate the use of improving and non-improving\nstrategies, and explore the relation between (non-)improvingness and\n(ε-) optimality. Improving strategies appear to play a very\nimportant role for obtaining ε optimality, while 0-optimal\nstrategies are always non-improving. Several examples are given to\nclarify all these issues

AB - In a zero-sum limiting average stochastic game, we evaluate a\nstrategy π for the maximizing player, player 1, by the reward φ\ns(π) that π guarantees to him when starting in state s.\nA strategy π is called non-improving if\nφs(π)⩾φs(π[h]) for any state s\nand for any finite history h, where π[h] is the strategy π\nconditional on the history h; otherwise the strategy is called\nimproving. We investigate the use of improving and non-improving\nstrategies, and explore the relation between (non-)improvingness and\n(ε-) optimality. Improving strategies appear to play a very\nimportant role for obtaining ε optimality, while 0-optimal\nstrategies are always non-improving. Several examples are given to\nclarify all these issues

U2 - 10.1109/CDC.1998.757857

DO - 10.1109/CDC.1998.757857

M3 - Chapter

SN - 0-7803-4394-8

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 2674

EP - 2679

BT - Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171)

ER -